Method of fabricating semiconductor cleaners

ABSTRACT

A method of manufacturing cleaning solvents is provided. The method includes selecting a small plurality of test solvents from a large plurality of perspective solvents. The equilibrium composition of a multi-component solution is preferably described by the Hansen solubility model. A small plurality of test solvents is applied to solute samples and the degree of dissolution or swelling recorded. Based on the degree of dissolution or swelling, at least one solvent is selected from the large plurality of perspective solvents based on the Hansen parameters. In other embodiments, the three-parameter Hansen solubility model includes additional parameters that enable more accurate solubility predictions. In one embodiment, an additional parameter accounts for oxidizing solution components. In an alternative embodiment, an additional parameter accounts for the acidic/basic property of the solution. Still another embodiment accounts for temperature effects.

This application claims the benefit of U.S. Provisional Application No.60/625,241, entitled “Method of Fabricating Semiconductor Cleaners,”filed on Nov. 5, 2004, and U.S. Provisional Application No. 60/672,331,entitled “Method of Fabricating Semiconductor Cleaners,” filed on Apr.18, 2005, which applications are hereby incorporated by reference intheir entirety.

TECHNICAL FIELD

This invention relates generally to semiconductor device manufacturingand more particularly to a method for fabricating cleaning or strippingsolvents for photoresists, dielectrics, processing residues, and othersoluble materials.

BACKGROUND

The semiconductor industry uses many cleaning solvents. For example, themanufacture of semiconductor components and integrated circuits iscarried out using photolithographic processes. Semiconductor substratesare coated with photoresists, developed, and patterned. After theseprocesses, the photoresist and process residues have to be removed. Forthis purpose, cleaners, solvents, or strippers are used.

Selection of a cleaner involves considering many factors such asvolatility, viscosity, acidity, surface tension, environmental, andhealth and safety. Another important factor is a cleaner's ability toadequately remove one material while leaving other materials unaffected.A major difficulty facing the user is the bewildering array of cleanersavailable, but a shortage of information to guide the user in selectinga cleaner that has the desired properties. The difficulty is compoundedwhen proprietary concerns prevent disclosure of the details concerningeither the cleaner or the application. Often both the chemical supplierand the semiconductor manufacturer are unwilling to disclose materialproperties because of the possibility of reverse engineering. Forexample, a semiconductor manufacturer may be unwilling to disclose thecomposition of an experimental photoresist or a new low-k dielectric. Insituations like this, the cleaner manufacturer can offer little guidanceto the user in selecting an appropriate cleaner or other solvent.

Determining the optimum cleaning solvent by trial and error is timeconsuming and expensive. Product literature and technical reports ofteninclude an enormous quantity of data, yet lack the ability to predictwhether a solvent will work in a given situation. Thermodynamic phaseequilibrium calculations are limited in value by their complexity andlack of suitable equilibrium solubility data, particularly for newmaterials.

In light of considerations such as these, there remains a need for amethod of efficiently selecting or producing cleaning solvents. There isa particular need in manufacturing applications where proprietaryconcerns prevent disclosure of a solvent or solute composition.

SUMMARY OF THE INVENTION

These and other problems are generally solved or circumvented, andtechnical advantages are generally achieved, by preferred embodiments ofthe present invention that provide a method for rapidly selecting asubset of promising cleaners from the universe of available solvents.Once a small group of promising solvents is selected, manufacturers maymore effectively allocate scarce resources for determining the optimumsolvent (or mixture of solvents) for a given application.

In preferred embodiments, a method of manufacturing cleaning solvents isprovided. The cleaning solvents may include a stripping solution forremoving a resist or dielectric residue from a semiconductor substrate,for example. A method includes compiling a database that includessolvents and solubility parameters for a large plurality of perspectivesolvents. The method further includes selecting a small plurality oftest solvents from the large plurality of perspective solvents. Thesmall plurality is preferably less than or equal to about 20, and thelarge plurality is preferably larger than about 200, and more preferablylarger than about 20,000. The equilibrium composition of amulti-component solution comprising the solute dissolved in the solventis preferably described by a predetermined plurality of parameters. Thesolute may comprise, for example, a material produced in a semiconductorfabrication process.

In preferred embodiments, the plurality of parameters includes Hansenparameters and a Hansen radius of interaction, such as those used in aHansen solubility model. In preferred embodiments, a small plurality oftest solvents is applied to solute samples and the degree of dissolutionor swelling recorded. Based on the degree of dissolution or swelling, atleast one solvent is selected from the large plurality of perspectivesolvents based on the Hansen parameters, thereby producing a newcleaning solvent.

In other embodiments, the Hansen solubility model includes additionalparameters that enable more accurate solubility predictions. In oneembodiment, an additional parameter accounts for oxidizing solutioncomponents. In an alternative embodiment, an additional parameteraccounts for the acidic/basic property of the solution. Still anotherembodiment accounts for temperature effects. In still other embodiments,one or more solubility parameters are extended by adjusting at least oneof a temperature, a surface tension, a redox potential, an acid content,a viscosity, and a fluoride concentration of the cleaning solvent.

Preferred embodiments provide a method of fabricating a cleaning solventfor removing a residue. Embodiments include calculating a set of solutesolubility parameters for the residue by combining the solventsolubility parameters for the test solvents in proportion to the amountof residue dissolved by each member of the small plurality of testsolvents. Embodiments may further include mixing at least two solventsfrom the large plurality of perspective solvents to form a mixture sothat the set of solvent solubility parameters for the mixtureapproximates the set of solute solubility parameters for the residue.

In other embodiments of the invention, calculating the set of solutesolubility parameters includes using a surface tension solubility model.Such a model includes constructing a free surface energy plot,calculating a polar free energy and a dispersive free energy of thesolute from the surface free energy plot.

Embodiments of the invention may further comprise using the calculatedsolubility parameters of the cleaning solvent to decide if a formulationis useful to remove a material. Still other embodiments may furthercomprise using the calculated cleaning parameters of the cleaningsolvent to compare different cleaning formulations.

Yet still other alternative embodiments further include an iterativeprocess for fully optimizing the cleaning solvent. Embodiments furtherinclude mixing a plurality of perspective solvents using an equilibriumsolubility model based on mole fraction.

Other embodiments of the invention provide a method of fabricating acleaning solvent for removing a residue. The method includes measuringan amount of the residue dissolved by each member of the small pluralityof test solvents, and calculating a set of solute solubility parametersfor the residue by combining the solvent solubility parameters for thetest solvents in proportion to the amount of residue dissolved by eachmember of the small plurality of test solvents. Preferably, measuring anamount of the residue dissolved comprises including a non-residue soluteadjacent a residue and determining a test solvent selectivity bymeasuring an amount of non-residue dissolved by the test solvent.Measuring an amount of the residue dissolved may comprise measuring aswelling of the residue.

An embodiment further comprises mixing at least two solvents from thelarge plurality of perspective solvents to form a mixture so that theset of solvent solubility parameters for the mixture approximates theset of solute solubility parameters for the residue.

Embodiments of the invention may further comprise adjusting at least oneof a temperature, a surface tension, a redox potential, an acid content,a viscosity, and a fluoride concentration of the cleaning solvent. Thesolvent and solute solubility parameters may comprise parameterscorresponding to the Hansen solubility model, or an alternative modelsuch as a surface tension model.

In the various embodiments, the cleaning solvent may comprise aphotoresist stripper, and the residue comprises a dielectric residue ora resist residue or another material generated or used in a process.

Other embodiments provide a method for fabricating a semiconductordevice. The method comprises forming an intermediate semiconductordevice on a substrate, wherein the forming includes generating amaterial to be removed using a cleaning solution. The method furtherincludes fabricating the cleaning solution. Preferably, the fabricatingcomprises selecting a small plurality of candidate solutions, whereineach member of the small plurality has a known solubility parameter,measuring an amount of swelling caused by each member of the smallplurality using a test sample of the material, and calculating a set ofsolute solubility parameters for the material by combining thesolubility parameters for the test solvents in proportion to the amountof the material dissolved by each member of the small plurality of testsolvents. Embodiments further comprise selecting a solvent from thelarge plurality of perspective solvents based on the set of solutesolubility parameters for the material, and removing the material usingthe cleaning solution.

Embodiments may further comprise mixing at least two solvents from thelarge plurality of perspective solvents to form a mixture so that theset of solubility parameters for the mixture approximates the set ofsolute solubility parameters for the residue. Other embodiments mayfurther comprise adjusting at least one of a temperature, a surfacetension, a redox potential, an acid content, a viscosity, and a fluorideconcentration of the cleaning solvent. Calculating the solubilityparameters of the cleaning solvent may include a solubility model, suchas Hansen or surface tension. In an embodiment, the material to beremoved by the cleaning solution comprises a material from a fabricationof a porous dielectric.

The foregoing has outlined rather broadly the features and technicaladvantages of the present invention in order that the detaileddescription of the invention that follows may be better understood.Additional features and advantages of the invention will be describedhereinafter which form the subject of the claims of the invention. Itshould be appreciated by those skilled in the art that the conceptionand specific embodiment disclosed may be readily utilized as a basis formodifying or designing other structures or processes for carrying outthe same purposes of the present invention. It should also be realizedby those skilled in the art that such equivalent constructions do notdepart from the spirit and scope of the invention as set forth in theappended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention, and theadvantages thereof, reference is now made to the following descriptionstaken in conjunction with the accompanying drawings, in which:

FIGS. 1 to 3 are Teas plots illustrating embodiments of the inventionthat provide a method for fabricating a cleaning solvent.

Corresponding numbers and symbols in different figures generally referto corresponding parts unless otherwise indicated. The figures are drawnto clearly illustrate the relevant aspects of the preferred embodimentsand are not necessarily drawn to scale. To more clearly illustratecertain embodiments, a letter indicating variations of the samestructure, material, or process step may follow a figure number.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

The making and using of the presently preferred embodiments arediscussed in detail below. It should be appreciated, however, that thepresent invention provides many applicable inventive concepts that maybe embodied in a wide variety of specific contexts. For example,embodiments of the invention are believed particularly advantageous forfabricating solvents useful in semiconductor manufacturing. The solventsmay include cleaners for removing materials such as residues, resists,impurities, reaction byproducts, or unwanted solids.

Preferred embodiments include using equilibrium solubility models knownin the chemical arts for predicting what solvent will have the bestcleaning properties. One suitable model is the Scatchard-Hildebrandtheory of regular solutions. Another is the Flory-Huggins model. TheHansen solubility model is especially preferred.

Sinha, S. and Achenie, L. E. K., “Systematic Design of Blanket WashSolvents with Recovery Considerations,” Advances in EnvironmentalResearch (2001), which is hereby incorporated by reference, describeusing the Hansen solubility model to select cleaning solvents for theprinting industry.

Briefly, the Hansen solubility model includes three parameters thataccount for dispersion, hydrogen bonding, and polar interactions insolutions. In Hansen's model, the three parameters for the solute andsolvent are used calculate a solubility sphere for that solute. A value,known in the chemical arts as an interaction radius, characterizes thesize of the sphere. The interaction radius and the three Hansenparameters are a function of the physical properties of the solute.Liquids whose Hansen parameters lie within the solute solubility spherewill dissolve that solute. Since 3D plots are inconvenient to work with,those skilled in the art frequently make a 2D plot by taking a slice ofdata taken from the solubility sphere. Such a plot, called a Teas plot(named for its developer), is well known in the chemical arts.

The format of a conventional Teas plot is illustrated in FIG. 1. TheTeas plot has three axes corresponding to the dispersion (δ_(D)),hydrogen bonding (δ_(H)), and polar (δ_(P)) parameters. The threeparameters are scaled so that the sum of their values is 100 (or 1,depending on the convention). A hypothetical solvent represented bypoint 120 in FIG. 1 illustrates how the Teas plot is read. As shown bythe bold lines in FIG. 1, point 120 represents a solvent having theparameter set: δ_(D)=50, δ_(H)=15, and δ_(P)=35. A particular advantageof the Teas plot is its usefulness in predicting the solubility behaviorof other solvents whose parameter set lies in a region near point 120.

Turning now to FIG. 2, an illustrative embodiment of a method formanufacturing a semiconductor cleaning solvent comprises the followingsteps. The method includes selecting a small plurality of test solventsfrom large plurality of perspective solvents. The small plurality ispreferably about 10 to about 20, although it may be smaller or larger.The large plurality is preferably larger than about 200, and morepreferably larger than about 20,000. For ease of illustration, theexemplary large plurality is only about 100. In actuality, there arethousands of solvents for which the Hansen parameters are known. Sinceit is impossible to test several thousand cleaning solvents or theirmixtures, a small plurality of solvents is selected from the largeplurality of perspective solvents. The small plurality comprises testsolvents that are used to develop a cleaning solution.

The equilibrium composition of a multi-component solution comprising thesolute dissolved in the solvent is preferably described by apredetermined plurality of solubility parameters. In preferredembodiments, the plurality of parameters includes Hansen parameters anda Hansen radius of interaction. In preferred embodiments, a smallplurality of test solvents is applied to solute samples and the degreeof dissolution or swelling recorded. Based on the degree of dissolutionor swelling, at least one solvent is selected from the large pluralityof perspective solvents based on the Hansen parameters, therebyproducing a new cleaning solvent.

In FIG. 2, solid squares represent the small plurality, and solidcircles represent the large plurality. In preferred embodiments, thesmall plurality is selected such that its distribution of solubilityproperties is representative of the large plurality. The Hansenparameters of the solvents are known, but parameters for the solute areunknown. The manufacturing process begins by performing cleaning testsusing the test solvents. On some samples, the test solvent will have noaffect. Rarely, others will yield a positive result characterized bysatisfactory dissolution of the material. With other samples, there willbe an intermediate response characterized by swelling, or partialdissolution, of the solute.

In a conventional method, even after finding that a given solvent causesswelling; a manufacturer is still faced with the daunting task ofnarrowing the field of perspective solvents. However, in preferredembodiments, the process is significantly improved. For example,consider the TEAS plot shown in FIG. 3. In FIG. 3, several solventsincluding one test solvent are circled. For illustrative purposes,assume that the test solvent is acetronitrile. As shown by FIG. 3, itssolvent parameter set is approximately: δ_(D)=38, δ_(H)=14, andδ_(P)=48. One sees that there are only a few perspective solvents, whichare circled, that are worth investigating. Advantages of embodiments aremore clearly realized by recognizing that the number of perspectivesolvents are, from a practical manufacturing point of view,prohibitively large to fully examine. Selecting candidate testingsolvents in view of their Hansen parameters rapidly streamlines theprocess.

Other embodiments dispense with the need for TEAS plotting by creating acomputer database of perspective solvents. Selection of solvents basedon test results may be done using conventional numerical methods, suchas interpolation, Householder's method for linear systems, or Newton'smethod for nonlinear systems.

Embodiments may further include the calculation of Hansen parameters formixtures of solvents. This embodiment is particularly advantageous whenusing a large computer database of solvents because the properties of asolution are frequently a nonlinear function of its individualcomponents. Therefore, embodiments may include a numerical iterativeprocess that includes the following steps. Based on the swelling testresults, the desired Hansen parameters of the target solvent areobtained, for example by interpolating the Hansen parameters of the testsolvents that yielded good results. If a solvent within the database hasthe target Hansen parameters, it is tested. If no suitable solventexists, perhaps because of toxicity concerns, two or more solvents maybe mixed. If the solvent is an ideal solution, the Hansen parameters ofthe mixture are accurately described by a linear combination of theindividual components. If the solution is non-linear, the Hansenparameters of the mixture may be more accurately approximated using avapor-liquid equilibrium model available in the chemical arts.

In embodiments wherein the Hansen parameters of the solute are known,the target cleaning solvent composition may be calculated directly.

Embodiments described herein may be conveniently inserted into asemiconductor manufacturing process. For example, an unanticipatedvariation in the manufacturing process may occur, such as a temperaturetransient in a furnace. The temperature transient may produce a changein photoresist solubility, for example. Rather than scrap an entire run,embodiments herein enable the manufacturer to rapidly change photoresiststrippers or even develop a new stripper to correct for the transient.

In alternative embodiments, the three-parameter Hansen solubility modelis extended by an additional parameter to account for acidity or by anadditional parameter to account for oxidizing or reducing agents. Sincemany solvents used in the semiconductor industry are non-aqueous, acideffects are more precisely described in embodiments using Lewis acidconcentration rather than pH. Preferably, the acidity is calculatedusing pK_(a) values, while a reducing/oxidizing (redox) parameter ismeasured in experiments or is calculated from redox potentials. Apreferable method to adjust the solution redox potential includes addinghydrogen peroxide or peroxo-acetic acid. Embodiments including the redoxpotential are useful, for example, when solvent performance isinfluenced by its acidity, such as in oxidation.

Both pH (or Lewis acidity) and redox parameters are particularly usefulin applications involving metals (e.g., copper) and their oxides. Incertain instances, copper removal is preferred, for example to improveresistance in a via chain. In other instances copper loss is to beavoided. Cleaner selectivity evaluation may include placing anon-residue solute adjacent a residue and measuring an amount ofnon-residue dissolved by the test solvent.

In other embodiments of the invention, the three-parameter Hansensolubility model is extended by an additional parameter to account forsurface tension or an additional parameter to account for viscosity.Such parameters are conveniently measured using conventional means.Embodiments comprising a viscosity solubility parameter are particularlyuseful when fluid convection is an important solvent consideration, suchas in a flow-through bath. Embodiments comprising the surface tensionsolubility parameter are particularly useful when good wetting isimportant. In other embodiments, the surface tension solubilityparameter may be expressed using the contact angle, a measurablequantity. In alternate embodiments, the surface tension of the cleanermay be adjusted using surfactants, which affect surface behavior withoutsignificantly changing bulk chemical properties.

In still other embodiments, the solubility model includes a fluorideactivity parameter and/or an etch rate solubility parameter. Thefluoride activity parameter may be calculated from concentrated fluoridesources, activity, and solubility data. The fluoride activity parameteris particularly useful in combination with the etch rate parameter.Therefore, the fluoride activity parameter and etch rate parameter maybe combined into a single parameter or further broken down intosub-parameters that account for temperature changes or deviations fromstandardized conditions.

Sometimes a good solvent may not be readily available. For example, agood solvent might be highly carcinogenic. Therefore, preferredembodiments solve this problem by adjusting the temperature of thesolution, generally a temperature increase. Gaps between suitableparameters could be overcome by the increase in temperature. Embodimentsincluding a temperature adjustment advantageously increase the threedimensional sphere of solubility. This causes a larger set ofperspective solvents to lie within this sphere.

As noted above, there are other solubility models than the Hansen model.Another embodiment of the invention includes a solubility model based onthe surface free energy of the solute. A basic requirement shared by allliquid cleaning methods is that the cleaning solvent must at leastpartially wet a surface of the solute. The parameters known to controlwettability include the solvent's surface tension, its contact anglewith the surface, and the properties of the surface. A particularlyrelevant surface property is its surface free energy. An embodiment ofthe invention includes characterizing the solute surface free energyusing liquids having a known surface tension.

An embodiment includes measuring the contact angle between at least twosolvents and the solute to be cleaned. The surface tension of thesolvents is preferably described in terms of a combination of a polarand dispersive component. The two components of the surface free energymodel may share a similar theoretical foundation as the analogousparameters in the Hansen solubility model; however, their values aregenerally not equal and are not to be confused.

The contact angle between a solvent having a known surface tension andthe solute is measured using conventional techniques. The data forseveral points are plotted using a surface free energy plot. For eachcontact angle measurement, a point in the plot is generated. They-coordinate is provided by the formula y={(1+cos(θ))/(2σ_(l)/√{squareroot over (σ_(l) ^(d))})} and the x-coordinate is provided by x=√{squareroot over (σ_(l) ^(p)/σ_(l) ^(d))}, which is a constant for each testedsolvent. Therefore, the tested liquids should be as different aspossible in the σ_(l) ^(p)/σ_(l) ^(d) ratio. The surface free energy ofthe solute is found using the slope and y-intercept: A=√{square rootover (σ_(s) ^(p))} and B=√{square root over (σ_(s) ^(d))}, wherein thepolar and dispersive component of the surface free energy are σ_(s) ^(p)and σ_(s) ^(d), respectively.

The total free energy of the surface is the sum of the polar anddispersive components. Having determined the polar and dispersivecomponents according to embodiments provided herein, an optimum cleaneris selected by matching the polar and dispersive components of thesolvent to the solute. For this purpose based on the known free surfaceenergy of the surface and the surface tension of the liquid (both indispersive and polar part), a potential contact angle may be calculated.Its value is preferably in the region between about 10 and 40 degrees.

In other embodiments, a customized cleaning solution is developed byblending a plurality of solvents. Preferably, the blending includescombining solvents having known solubility parameters. The solubilityparameters of the resulting blend may be predicted based on the molefraction of the individual solvents comprising the combination.Embodiments may include blending or adding materials not normallyconsidered solvents, like salts, for example.

In summary, solvent selection comprises the following steps. A pluralityof test cleaning solutions having known solubility parameters isselected. The solubility parameter of multi-component cleaning solutionsmay be calculated using the molar fraction of the components. Thematerial to be removed, i.e., dissolved, is treated with differentchemicals or mixtures of known Hansen parameters.

In photoresist removal, for example, cleaning effectiveness is evaluatedby characterizing the amount of photoresist swelling in a given time. Onsome samples, the solvent will have no affect. Others will yield apositive result characterized by dissolution of the material. With othersamples, there will be an intermediate response characterized byswelling of the solute. In systems with poor or intermediate results,the solubility sphere may be adjusted by raising the temperature, addingan oxidizing or reducing agent, adjusting the fluoride content, oradding a surfactant to change surface tension, for example.

By localizing the solvent testing domain, multiple solutions, mayrapidly be investigated and the composition of a target cleaning solventcalculated using suitable numerical methods. Solutions or blends ofsolvents can be calculated to circumvent toxicity, unavailability,environmental or other critical issues of some chemicals, by molecularfraction and individual parameter sets. The solution could be fortifiedby improving the availability of Lewis acids and bases or the oxidizingcapabilities. Other chemical/physical properties like viscosity, surfacetension, etc., could be modified by exchanging chemicals, yet stillkeeping the desired parameter set in focus.

Embodiments described herein have other applications that do not involvecomparing chemicals for cleaning solutions. One such applicationincludes semiconductor manufacturing involving low-k dielectrics.

Low-k dielectrics are an important component in many semiconductordevices. Since air has a dielectric constant of about 1, one method formaking low-k dielectrics incorporates air into dense materials to makethem porous. The dielectric constant of the resulting porous material iscombination of the dielectric constant of air and the dielectricconstant of the dense material. One way of making porous dielectrics isto include a pore generating material (a porogen) in a low-k dielectric.At a suitable stage in device manufacture, dielectric pores aregenerated, usually by thermal degradation of the porogen.

There are two processing routes commonly used in low-k dielectricmanufacture. These are frequently referred to as the solid first routeand the porous first route. Both routes are commonly used in the dualdamascene process, for example. In the porous first route, thedielectric is deposited and made porous before the dual damascenetrenches and vias are patterned and copper filled. In the solid firstroute, the dielectric is deposited, patterned, copper filled, and thenmade porous. An important consideration for selecting one route over theother is potential contamination of the pores with pore generationbyproducts, which degrade the low-k dielectric. Another consideration isthe higher surface area of porous material and the increased risks ofsurface contamination or damage.

Using embodiments described herein, Hansen, redox, etching, surfacetension and other parameters guide the decision as to which poregeneration route to take. For example, the pore generation process mayinclude chemical extraction of the porogen from the dielectric matrix.Comparison of the solubility parameters for the solvent, the porogen,and the dielectric matrix will determine whether one or anothercomponent is sensitive to chemical attachment, such asoxidation/reduction, or acid/base reactions.

Embodiments of the invention described above may be included in solventevaporation or drying processes. For example, in a solvent drying step,a mass loss vs. temperature plot may characterize the amount andproperties of the unevaporated material. For example, if after using thehighest possible drying temperature, a residue remains, a solvent orcleaner provided by embodiments provided herein may remove the residue.Information about boiling or evaporation behavior may be included in adatabase of mass loss, temperature, and/or other parameters like surfacetension. Such information may be used to estimate the composition in aspinning process or in open storage over time.

Although the present invention and its advantages have been described indetail, it should be understood that various changes, substitutions andalterations may be made herein without departing from the spirit andscope of the invention as defined by the appended claims. For example,it will be readily understood by those skilled in the art that materialsand methods may be varied while remaining within the scope of thepresent invention. It is also appreciated that the present inventionprovides many applicable inventive concepts other than the specificcontexts used to illustrate preferred embodiments. Accordingly, theappended claims are intended to include within their scope suchprocesses, machines, manufacture, compositions of matter, means,methods, or steps.

What is claimed is:
 1. A method of selecting a cleaning solventcomprising: compiling a database that includes solvents and solubilityparameters for a large plurality of perspective solvents; selecting fromthe large plurality of perspective solvents, a small plurality of testsolvents; performing dissolution tests on a solute using the smallplurality of test solvents, wherein the solute comprises a material in asemiconductor manufacturing process; calculating the solubilityparameters of the cleaning solvent based on the dissolution tests; andselecting the cleaning solvent from the database of solubilityparameters using the calculated solubility parameters of the cleaningsolvent.
 2. The method of claim 1, wherein calculating the solubilityparameters of the cleaning solvent includes using a Hansen solubilitymodel.
 3. The method of claim 2, wherein the Hansen solubility modelincludes a parameter describing the acidity of the solvent.
 4. Themethod of claim 2, wherein the Hansen solubility model includes aparameter describing the redox potential of the solvent.
 5. The methodof claim 2, wherein the Hansen solubility model includes a temperatureadjustment.
 6. The method of claim 1, wherein selecting a cleaningsolvent from the database includes mixing at least two solvents.
 7. Themethod of claim 6, wherein mixing at least two solvents comprisesforming a mixture so that a set of solubility parameters for the mixtureapproximates a set of solubility parameters for the solute.
 8. Themethod of claim 7, wherein the set of solubility parameters are used ina Hansen solubility model.
 9. The method of claim 1, wherein thecleaning solvent is a photoresist stripper.
 10. The method of claim 1,wherein the small plurality is less than about
 20. 11. The method ofclaim 1, wherein the large plurality is greater than about
 200. 12. Themethod of claim 1, wherein calculating the solubility parameters of thecleaning solvent includes using a surface tension solubility model. 13.The method of claim 12, wherein the surface tension solubility modelcomprises: constructing a free surface energy plot; calculating a polarfree energy and a dispersive free energy of the solute from the surfacefree energy plot.
 14. The method of claim 1, further comprising usingthe calculated solubility parameters of the cleaning solvent to decideif a formulation is useful to remove a material.
 15. The method of claim1, further comprising using the calculated solubility parameters of thecleaning solvent to compare different cleaning formulations.
 16. Themethod of claim 2, wherein the Hansen solubility model includes aparameter to account for surface tension.
 17. The method of claim 2,wherein the Hansen solubility model includes a parameter to account forviscosity.
 18. The method of claim 2, wherein the Hansen solubilitymodel includes a fluoride activity parameter.
 19. The method of claim 2,wherein the Hansen solubility model includes an etch rate solubilityparameter.